For the nerds

“Starving the Watchdog” (3/16/19)

Who has a subscription to a local newspaper? *crickets* I don’t think I’ve ever had a subscription to a local newspaper. I believe my neighbors have a subscription just for the coupons featured in the Sunday paper. Today, news (or fake news) just gets delivered to our fingertips, and millions of Americans have decided they don’t need to pay for a subscription to the local newspaper anymore. If nobody is reading the paper, businesses aren’t going to pay for advertisements in the paper. Without advertisements in the paper, local newspaper revenues plummet and the business has to downsize by cutting staff or shut down all together. I didn’t really think about this much, but came across a podcast that was really informative about the broader effects of the decline of local journalism as Americans move away from print media.

Local newspapers provide the stories cited by so many other aggregators, like news channels or even the more popular online news sources. In John Oliver’s words, “it’s pretty obvious, without newspapers around to cite, TV news would just be Wolf Blitzer endlessly batting a ball of yarn around.” LOL. On top of that, local newspapers act like local police departments by standing up to corruption in local government and business (have you seen Spotlight!? If not, highly recommend.). In fact, new research shows that there’s a price to be paid by taxpayers when these local watchdogs shutter down. Following a newspaper closure, municipal borrowing costs increase by .05-.11%, which roughly translates to $650k for every issuance. The rise in corruption causes municipalities to become riskier in the eyes of lenders, which raises their cost of borrowing money, which falls on the shoulders of the taxpayers that have stopped subscribing to local newspapers.

The Laffer Curve (3/9/19)

It seems almost impossible to tune into the news these days and not pick up on taxes in some way – whether it’s about raising taxes on the wealthy or about the impact of tax reform on tax returns (or lack thereof). And at this point in the political cycle, this is bound to be a politicized topic of conversation. At the end of the day, taxes are meant to generate revenue to fund the government, so the question becomes – at what point is the tax system most efficient at raising revenues while stimulating economic growth? Here, I find Art Laffer’s views interesting. He first explained the concept of his famous Laffer Curve on the back of a napkin in the early 1970s and it’s meant to demonstrate the relationship between tax rates and the amount of tax revenue collected by the government.

The Laffer Curve shows that as taxes increase from 0%, tax revenue generated for the government also increases. However, increasing taxes beyond a certain threshold diminishes the incentive to work or produce more, at which point continuing to increase taxes actually reduces output, and therefore, the amount of tax revenue. And when you tax a person or a company at 100%, they’re going to just stop working and producing, which means they are now generating no income on which to actually pay taxes, so the government’s tax revenues are also 0. Hence, tax revenues as a function of the tax rate follow a curve – they start at 0, increase until you reach that threshold tax rate, and then decrease back to 0. Yes, this concept is potentially too simplistic, but it provides a basic framework when thinking about the effectiveness of tax policies.

From the Oracle of Omaha (3/2/19)

A few years ago, I read The Essays of Warren Buffett, a book that compiles excerpts from Warren Buffett’s annual letter to Berkshire Hathaway’s shareholders. Since then, I’ve made it a habit to read the annual letters – they’re never too long and always prove to be witty and informative in true Warren Buffett style. This year’s letter was published earlier this week and these are my favorite points:

“Abraham Lincoln once posed the question: ‘If you call a dog’s tail a leg, how many legs does it have?’ and then answered his own query: ‘Four, because calling a tail a leg doesn’t make it one.’ Abe would have felt lonely on Wall Street.” First of all, I laughed out loud. Second of all, I couldn’t agree more – this is in the part of the letter titled “Focus on the Forest – Forget the Trees” and the example Warren uses here is fitting – companies not considering stock-based compensation as an expense – “What else could it be? A gift from shareholders?” So many companies and Wall Street analysts try to cloud the view of the forest by manipulating the minutia of the trees – always step back and look at the big picture when analyzing investments. When you invest in a company, you’re investing in its management team and a management team that calls a tail a leg is usually not one to trust in.

Viewing the US government as a shareholder at an ownership percentage based on the tax rate. YAAASS!!! Of course when you say it, it makes total sense, but I hadn’t ever really thought of it in this way specifically! If lawmakers would view themselves as 21% owners (based on the new corporate tax rate) in companies, and educate themselves on how capital markets actually work, there would be no talk about eliminating or limiting share buybacks. That’s a whole another topic (read: rant) for another week.

“The American Tailwind” – This country, in a truly bipartisan way (under the leadership of 7 Democratic and 7 Republican Presidents), has seen the stock market turn $1 into $5,288 over the last 77 years since Warren Buffett made his first investment. Warren Buffett attributes a lot of his success on this country that started with a “small band of ambitious people…aimed at turning their dream into reality. Today, the Federal Reserve estimates our household wealth at $108 trillion, an amount almost impossible to comprehend.” Cue USA chant. I can’t wait to be part of the next 77 years of American growth.

Abundance (2/23/19)

“Capitalism, at its core, is fairly straightforward: create shareholder value by providing customers with access to something scarce.” But software and the internet have decimated so many barriers to scarcity in industry after industry (retail, content, etc.) that we’re entering a new world of abundance – where the friction involved in consumption decisions starts to disappear. This week I came across Alex Danco’s thoughts on industry structures and competitive behavior and how they’re changing as we shift from a world of scarcity to a world of abundance.

If you’re willing to spend some time on it, I’d highly recommend reading the essays in their entirety but here are his punchlines:

Friction (scarcity) allows for return on capital while the lack of friction (abundance) allows for compounding growth – great businesses harness both.

Technology changes where the friction is located – as scarce resources become abstracted and turn abundant, scarcity appears elsewhere.

Scarcity motivates us to act for the long term by solving hard problems but when it’s unclear what is scare, short-term thinking takes over, which makes us greedy when we should be fearful and fearful when we should be greedy.

Closing the Loop (2/16/19)

An interesting concept called a “circular economic model” came across my reads this week. I found many different definitions of this concept, but essentially it’s an industrial system that’s regenerative by design – it is intended to eliminate waste as products are designed to be reused and the energy consumed throughout the industrial process is renewable by nature. For example, Rothys makes shoes from recycled water bottles and offers customers free shipping to return used shoes that can be recycled into yoga mats, soles, or even new shoes. A recent survey from ING indicated that 16% of US companies are already adopting circular economies while another 62% of US companies are moving toward a circular economy as part of their future business strategy.

Rewind and Rewrite (2/9/19)

Ever think about something that happened in your life and then think of a thousand different things you could have said or done differently to generate a different outcome? I learned this week that this kind of thinking actually has a technical name – it’s called a counterfactual and is triggered by four elements of the specific memory –

It is clearly a bad outcome

It is out of the ordinary

You can see how you or somebody else had a central role in the outcome

You can draw a direct cause and effect relationship between what you or somebody else did (#3) and the clearly bad outcome (#1).

Counterfactuals are useful because they can help us see what we can do differently next time and help us feel like we can have more control over future outcomes – they can affect behavioral changes. An interesting podcast I heard this week analyzed why the lack of these triggers might explain apathetic behavior toward climate change.

Results of climate change (think receding glaciers or slowly rising water temperatures) are not seen by many as “end of the world” issues, so they don’t think of them as clearly bad outcomes, and for a lot of people, they aren’t anything out of the ordinary. Additionally, it can be difficult to pinpoint how any one action by an individual directly impacts climate change given it happens at a pace that’s not easily observable. Therefore, it’s difficult to directly observe a cause and effect relationship. The outcome – it doesn’t result in behavioral changes. If you’re passionate about climate change, here’s some food for thought – how can you create these triggers to actually influence others’ behaviors?

The Learning Curve (2/2/19)

You may or may not have gathered how fascinated I am by technological innovation, which, by definition, is brand new territory and therefore difficult to truly evaluate from a financial perspective. Investors determine the attractiveness of an investment based on its underlying value – how do you even think about assigning value to something that hasn’t existed before or is expected to see massive technological disruption? Enter Wright’s Law.

First published in 1936 in the Journal of Aeronautical Sciences, Wright’s Law tries to explain the rate of technological progress and basically tells us that we learn by doing (shocker, I know – fool me once…) and predicts that every percentage increase in the cumulative production results in a fixed percentage improvement in the production efficiency, or the unit cost. A study by MIT and the Santa Fe Institute actually found Wright’s Law to be the best model to forecast technological progress (out of a few that are out there) in various different industries from aircraft production to beer manufacturing. So apparently, to predict how the cost of a product is going to change through technological innovation (which is very useful in creating cash flow forecasts and valuing investments), I just have to figure out the historical rate at which technology has allowed things to get cheaper in that industry (for example, computers) and apply that same rate going forward. Magic.

Life Tips (1/26/19)

This week goes out to one of my favorite books – it resonates with me in ways few others ever have – The Tipping Point by Malcolm Gladwell. In the broadest sense, the book is about the ability of small changes to make huge differences. It explores social epidemics – when ideas, products, messages, or other behaviors in general – become popular suddenly and unexpectedly, and almost seem to happen overnight. The moment at which a social epidemic goes from being invisible to inevitable is called the “tipping point” (based on the diffusion of innovation, remember this concept from a few weeks ago?) and this book explores how these social epidemics happen and whether it’s actually possible to start and control them.

The book explores social epidemics via three concepts – the people who cause them, the actual content of the epidemics, and the environment in which they occur:

Law of the Few: A small number of people have a disproportionate amount of power. Social epidemics reach a tipping point when Mavens (those who love to accumulate knowledge and therefore discover the trend) tell Connectors (those with with massive networks with the ability and propensity to spread information they feel important), who end up telling the Salesmen (those who can persuade people to change their behaviors).

Stickiness: Unless the idea or product or behavior is “sticky” – memorable enough to make people take action. The example – Sesame Street. The amount of research that went into making the show is fascinating.

Context: human behavior is largely driven by the physical environment in which we live. This seems super intuitive, but the book uses poignant examples like the broken windows theory and Dunbar’s number to explain human behavioral changes in the face of changing contexts in a really impactful way.

I can’t tell you the number of times I’ve read this book, but every time I walk away wanting to be part of bringing a social epidemic to its tipping point. It’s an easy read and 110% worth every minute of the four hours (at most) it would take to get through it. Highly recommend. We can geek out about it after you’re done.

I Can Transform Ya (1/19/19)

Something that I absolutely love following in the market is disruptive innovation – products or services that will transform how we live and work. It provides a look into what the future holds, which helps me understand what companies out there will be long-term winners and losers of these transformations. Some of the most interesting disruptive innovation is happening in artificial intelligence, especially deep learning, which has the ability to transform every industry. Think of deep learning as a form of artificial intelligence inspired by a human brain – using deep learning, machines don’t need a programmer to tell them what to do, they use data to train themselves.

We’re already using products and services that are powered by deep learning – Facebook and Netflix leverage this to select custom content for users, the Apple Watch leverages this to predict arterial fibrillation, Tesla’s Model 3 autopilot uses this to drive on highways, Google Translate uses this to translate more than 100 billion words per day. Deep learning reaches into every industry and according to Ark Invest, could create 3x the value of the internet aka add $30 trillion to the global equity markets. This growth is powered by an unfathomable amount of data – and processing that much data creates a huge demand for computing hardware like AI chips and semiconductors. Stay tuned for some stock picks in this space, but this week I looked at AI-enabled cyber security platform provider Palo Alto Networks.

A Chess Master’s Views on Finance (1/12/19)

Thanks to one of our readers, Ryan DuBiel, for this week’s interesting find – a podcast featuring Adam Robinson – author, educator, hedge fund advisor, co-founder of The Princeton Review, a rated chess master with an undergrad degree from Wharton and a law degree from Oxford. TLDR, this dude’s really smart and I found two points he made to be really interesting:

First, in the world of finance, we talk about trends all the time. But how do we actually define that term? Adam defines it as the spread of ideas. He also references the diffusion of innovation as the method in which ideas spread (aka how trends appear) even within the stock market. I can discuss the diffusion of innovation for days, I’ll save that topic for another week.

Second, there are five groups of traders who express their views of the future in the way they trade – equity, currency, bond, metal, and energy traders – and below are Adam’s most interesting observations –

When bond traders and equity traders disagree about the economy, bond traders are usually right and early.

Bond traders’ views on the economy are expressed by the yield spread between corporate bonds and 10-year treasuries. Corporate bonds should have a higher yield than US treasuries – the smaller the spread, the stronger the economy. In the stock market, the higher the stock prices, the stronger the economy. So when you see a divergence in the views of the economy expressed by bonds and stocks, Adam says that 99% of the time, the views expressed by bonds are correct and early. My two cents – a bond investor’s method for analyzing a company is much more of a science than that of a stock investor’s just given the different risk/reward characteristics of bonds and stocks. Therefore, by default (pun intended), the bond investor’s method for analyzing a company should yield fewer errors that are introduced by various different biases in a stock investor’s method.

Metal traders are better than bond traders at predicting the direction of interest rates.

Metal traders view the economy in terms of how much copper is being sold – higher the copper sales, stronger the economy. Their effective interest rate is the price of copper divided by the price of gold. When we see this effective interest rate moving in the opposite direction of actual interest rates measured by 10-year treasuries, the interest rate directionality predicted by the metal traders’ effective interest rate has not been incorrect in this century. In August, the effective interest rate as shown by metal traders was at a one-year low, indicating interest rates should move down, while 10-year treasuries were indicating interest rates were at five-year highs above 3%. Since then, interest rates on 10-year treasuries have come down to about 2.7% and metal traders’ effective interest rates have maintained their perfect batting average.

The Essentials (1/5/19)

One of my absolute favorite books on investing is One Up on Wall Street by Peter Lynch. Peter Lynch managed the Magellan Fund at Fidelity Investments between 1977 and 1990. He averaged a 29.2% annual return (which is jaw-dropping awesome btw), more than doubling the S&P 500 market index consistently, and was largely regarded as the best mutual fund manager in the world.

For those of you who are really interested, I’d highly recommend reading the book in its entirety – it’s about 280 pages and filled with great lessons for the average investor and plenty of LOL moments. I read this book at least once a year and learn something new every time. Here are some of the biggest takeaways:

Invest with a long-term view. These lessons are probably my favorite.

Once you buy the stock, sell it once your reason to own the stock changes, not just because of price reactions in the market. Be patient and let the reason you bought the stock actually play out.

Buy when everyone is selling (aka when the stock price drops) – take advantage of your stock being on sale! But at the same time, don’t buy a company just because it seems cheap, you should believe in the company and not just blindly follow the numbers.

“If you can’t convince yourself ‘When I’m down 25 percent, I’m a buyer’ and banish forever the fatal thought ‘When I’m down 25 percent, I’m a seller,’ then you’ll never make a decent profit in stocks.”

Study and notice companies that you come across in your daily life – it’s the best way to identify good stocks, and usually before that information makes it to Wall Street.

Know what kind of investor you are before you invest in stocks. Know how you’re going to react when the market goes down 25%. And don’t invest with money that you can’t stomach losing.